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Le Cunff AL, Glover C, Martis BL, Giampietro V, Dommett E. Methodological adjustments for experimental studies including neurodiverse participants: A checklist for before, during, and after laboratory visits. MethodsX 2024; 12:102658. [PMID: 38510933 PMCID: PMC10950872 DOI: 10.1016/j.mex.2024.102658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 03/08/2024] [Indexed: 03/22/2024] Open
Abstract
In this paper, we developed an experimental checklist for laboratory experiments including neurodiverse participants, particularly those with attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and dyslexia. The checklist suggests additions to the basic requirements for ethical laboratory-based studies with human participants. The suggestions emphasize physical comfort, the agency of participants concerning environmental adjustments, clarity of communication, and a focus on participants' overall well-being. Those methodological guidelines aim to help researchers in facilitating inclusive and accessible laboratory environments for neurodiverse participants in order to: •Enhance research validity by minimizing the influence of factors that affect responses in neuroscience experiments.•Facilitate research recruitment by encouraging continued participation in future studies and increasing word-of-mouth.•Improve research dissemination by fostering a more positive perception of the research process amongst neurodiverse individuals and encouraging community involvement.
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Affiliation(s)
- Anne-Laure Le Cunff
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AB, United Kingdom
| | - Caitlin Glover
- School of Engineering and Informatics, University of Sussex, Brighton, BN1 9RH, United Kingdom
| | - Brandon-Lee Martis
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AB, United Kingdom
| | - Vincent Giampietro
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AB, United Kingdom
| | - Eleanor Dommett
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AB, United Kingdom
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2
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Radhoe TA, van Rentergem JAA, Torenvliet C, Groenman AP, van der Putten WJ, Geurts HM. Comparison of network structures between autistic and non-autistic adults, and autism subgroups: A focus on demographic, psychological, and lifestyle factors. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2024; 28:1175-1189. [PMID: 37776020 PMCID: PMC11067416 DOI: 10.1177/13623613231198544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/01/2023]
Abstract
LAY ABSTRACT There are large differences in the level of demographic, psychological, and lifestyle characteristics between autistic and non-autistic adults but also among autistic people. Our goal was to test whether these differences correspond to differences in underlying relationships between these characteristics-also referred to as network structure-to determine which characteristics (and relationships between them) are important. We tested differences in network structure in (1) autistic and non-autistic adults and (2) two previously identified subgroups of autistic adults. We showed that comparing networks of autistic and non-autistic adults provides subtle differences, whereas networks of the autism subgroups were similar. There were also no sex differences in the networks of the autism subgroups. Thus, the previously observed differences in the level of characteristics did not correspond to differences across subgroups in how these characteristics relate to one another (i.e. network structure). Consequently, a focus on differences in characteristics is not sufficient to determine which characteristics (and relationships between them) are of importance. Hence, network analysis provides a valuable tool beyond looking at (sub)group level differences. These results could provide hints for clinical practice, to eventually determine whether psychological distress, cognitive failures, and reduced quality of life in autistic adults can be addressed by tailored support. However, it is important that these results are first replicated before we move toward intervention or support.
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Affiliation(s)
| | | | | | | | - Wikke J van der Putten
- University of Amsterdam, The Netherlands
- Leo Kannerhuis (Youz/Parnassia Groep), The Netherlands
| | - Hilde M Geurts
- University of Amsterdam, The Netherlands
- Leo Kannerhuis (Youz/Parnassia Groep), The Netherlands
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3
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Choi EJ, Vandewouw MM, Taylor MJ, Stevenson RA, Arnold PD, Brian J, Crosbie J, Kelley E, Liu X, Jones J, Lai MC, Schachar RJ, Lerch JP, Anagnostou E. Dorsal Striatal Functional Connectivity and Repetitive Behavior Dimensions in Children and Youths With Neurodevelopmental Disorders. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:387-397. [PMID: 38000717 DOI: 10.1016/j.bpsc.2023.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 10/20/2023] [Accepted: 10/30/2023] [Indexed: 11/26/2023]
Abstract
BACKGROUND Impairing repetitive behaviors are one of the core diagnostic symptoms in autism spectrum disorder and obsessive-compulsive disorder, but they also manifest in attention-deficit/hyperactivity disorder. Although the dorsal striatal circuit has been implicated in repetitive behaviors, extensive heterogeneity in and cross-diagnostic manifestations of these behaviors have suggested phenotypic and likely neurobiological heterogeneity across neurodevelopmental disorders (NDDs). METHODS Intrinsic dorsal striatal functional connectivity was examined in 3 NDDs (autism spectrum disorder, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder) and typically developing control participants in a large single-cohort sample (N = 412). To learn how diagnostic labels and overlapping behaviors manifest in dorsal striatal functional connectivity measured with functional magnetic resonance imaging, the main and interaction effects of diagnosis and behavior were examined in 8 models (2 seed functional connectivity [caudate and putamen] × 4 sub-behavioral domains [sameness/ritualistic, self-injury, stereotypy, and compulsions]). RESULTS The obsessive-compulsive disorder group demonstrated distinctive patterns in visual and visuomotor coordination regions compared with the other diagnostic groups. Lower-order repetitive behaviors (self-injury and stereotypy) manifesting across all participants were implicated in regions involved in motor and cognitive control, although the findings did not survive effects of multiple comparisons, suggesting heterogeneity in these behavioral domains. An interaction between self-injurious behavior and an attention-deficit/hyperactivity disorder diagnosis were observed on caudate-cerebellum functional connectivity. CONCLUSIONS These findings confirmed high heterogeneity and overlapping behavioral manifestations in NDDs and their complex underlying neural mechanisms. A call for diagnosis-free symptom measures that can capture not only observable symptoms and severity across NDDs but also the underlying functions and motivations of such behaviors across diagnoses is needed.
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Affiliation(s)
- Eun Jung Choi
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Psychology, Western University, London, Ontario, Canada.
| | - Marlee M Vandewouw
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Margot J Taylor
- Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada; Departments of Psychology and Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Ryan A Stevenson
- Department of Psychology, Western University, London, Ontario, Canada; Brain and Mind Institute, Western University, London, Ontario, Canada
| | - Paul D Arnold
- Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Jessica Brian
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer Crosbie
- Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Elizabeth Kelley
- Department of Psychology and Centre for Neuroscience Studies, Queens' University, Kingston, Ontario, Canada; Department of Psychiatry, Queen's University, Kingston, Ontario, Canada
| | - Xudong Liu
- Department of Psychiatry, Queen's University, Kingston, Ontario, Canada
| | - Jessica Jones
- Department of Psychiatry, Queen's University, Kingston, Ontario, Canada
| | - Meng-Chuan Lai
- Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Azrieli Adult Neurodevelopmental Centre, and Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Russell J Schachar
- Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Jason P Lerch
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Evdokia Anagnostou
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Neurosciences & Mental Health, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
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4
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Waldren LH, Leung FYN, Hargitai LD, Burgoyne AP, Liceralde VRT, Livingston LA, Shah P. Unpacking the overlap between Autism and ADHD in adults: A multi-method approach. Cortex 2024; 173:120-137. [PMID: 38387375 DOI: 10.1016/j.cortex.2023.12.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 12/11/2023] [Accepted: 12/18/2023] [Indexed: 02/24/2024]
Abstract
The overlap between Autism and Attention-Deficit Hyperactivity Disorder (ADHD) is widely observed in clinical settings, with growing interest in their co-occurrence in neurodiversity research. Until relatively recently, however, concurrent diagnoses of Autism and ADHD were not possible. This has limited the scope for large-scale research on their cross-condition associations, further stymied by a dearth of open science practices in the neurodiversity field. Additionally, almost all previous research linking Autism and ADHD has focused on children and adolescents, despite them being lifelong conditions. Tackling these limitations in previous research, 5504 adults - including a nationally representative sample of the UK (Study 1; n = 504) and a large pre-registered study (Study 2; n = 5000) - completed well-established self-report measures of Autism and ADHD traits. A series of network analyses unpacked the associations between Autism and ADHD at the individual trait level. Low inter-item connectivity was consistently found between conditions, supporting the distinction between Autism and ADHD as separable constructs. Subjective social enjoyment and hyperactivity-impulsivity traits were most condition-specific to Autism and ADHD, respectively. Traits related to attention control showed the greatest Bridge Expected Influence across conditions, revealing a potential transdiagnostic process underlying the overlap between Autism and ADHD. To investigate this further at the cognitive level, participants completed a large, well-powered, and pre-registered study measuring the relative contributions of Autism and ADHD traits to attention control (Study 3; n = 500). We detected age- and sex-related effects, however, attention control did not account for the covariance between Autism and ADHD traits. We situate our findings and discuss future directions in the cognitive science of Autism, ADHD, and neurodiversity, noting how our open datasets may be used in future research.
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Affiliation(s)
| | | | | | | | - Van Rynald T Liceralde
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
| | - Lucy A Livingston
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Punit Shah
- Department of Psychology, University of Bath, Bath, UK.
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Sommers L, Papadopoulos N, Fuller-Tyszkiewicz M, Sciberras E, McGillivray J, Howlin P, Rinehart N. The Connection Between Sleep Problems and Emotional and Behavioural Difficulties in Autistic Children: A Network Analysis. J Autism Dev Disord 2024:10.1007/s10803-024-06298-2. [PMID: 38526802 DOI: 10.1007/s10803-024-06298-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/17/2024] [Indexed: 03/27/2024]
Abstract
The interactions between sleep problems, autism symptoms and emotional and behavioural difficulties were explored using network analysis in 240 autistic children (mean age: 8.8 years, range 5-13 years) with moderate to severe sleep problems. Findings revealed a highly connected and interpretable network, with three separate clusters identified of the modelled variables. Depression, anxiety and behavioural difficulties were the most central variables of the network. Depression, anxiety and restricted repetitive and stereotyped patterns behaviours (RRBs) were the strongest bridging variables in the network model, transmitting activation both within and between other symptom clusters. The results highlight that depression and anxiety were highly connected symptoms within the network, suggesting support in these areas could be helpful, as well as future research.
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Affiliation(s)
- Lucy Sommers
- School of Psychology, Faculty of Health, Deakin University, 1 Gheringhap Street, Geelong, VIC, 3220, Australia.
- School of Psychology, Deakin University, 221 Burwood Hwy, Burwood, VIC, 3125, Australia.
| | - Nicole Papadopoulos
- Monash Krongold Clinic, Faculty of Education, Monash University, 19 Ancora Imparo Way, Clayton, VIC, 3800, Australia
- School of Educational Psychology and Counselling, Faculty of Education, Monash University, 19 Ancora Imparo Way, Clayton, VIC, 3800, Australia
| | - Matthew Fuller-Tyszkiewicz
- School of Psychology, Faculty of Health, Deakin University, 1 Gheringhap Street, Geelong, VIC, 3220, Australia
| | - Emma Sciberras
- School of Psychology, Faculty of Health, Deakin University, 1 Gheringhap Street, Geelong, VIC, 3220, Australia
- Murdoch Children's Research Institute, 50 Flemington Road, Parkville, VIC, 3052, Australia
- Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, VIC, 3010, Australia
| | - Jane McGillivray
- School of Psychology, Faculty of Health, Deakin University, 1 Gheringhap Street, Geelong, VIC, 3220, Australia
| | - Patricia Howlin
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Nicole Rinehart
- Monash Krongold Clinic, Faculty of Education, Monash University, 19 Ancora Imparo Way, Clayton, VIC, 3800, Australia
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Dell’Osso L, Nardi B, Bonelli C, Amatori G, Pereyra MA, Massimetti E, Cremone IM, Pini S, Carpita B. Autistic Traits as Predictors of Increased Obsessive-Compulsive Disorder Severity: The Role of Inflexibility and Communication Impairment. Brain Sci 2024; 14:64. [PMID: 38248279 PMCID: PMC10813392 DOI: 10.3390/brainsci14010064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 12/30/2023] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
Due to similar manifestations, some authors have proposed a potential correlation between autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD). This link has long been recognized and debated, with some authors arguing that these disorders frequently occur comorbid but distinct while others believe they are part of the same spectrum. The aim of our study was to explore the prevalence and correlates of autistic traits in 55 OCD patients and 55 matched controls and to assess possible autistic dimensions predictive of higher OCD symptoms. All participants were assessed with the Obsessive-Compulsive Spectrum-Short Version (OBS-SV) and the Adult Autism Subthreshold Spectrum (AdAS Spectrum). The OCD group scored significantly higher in both questionnaires. Total OBS-SV scores and domains were significantly correlated with all AdAS Spectrum domains and total score. The AdAS Spectrum total, Verbal Communication and Inflexibility and adherence to routine domain scores were significant positive predictors of higher OBS-SV scores. Lastly, when two clusters of subjects (high and low autism) were determined, Inflexibility and adherence to routine domain presented the greatest influence in forming the clusters. Our findings support the association between OCD and autistic traits in the adult population, supporting the hypothesis of a neurodevelopmental basis for these psychiatric conditions.
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Affiliation(s)
- Liliana Dell’Osso
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Benedetta Nardi
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Chiara Bonelli
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Giulia Amatori
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Maria Alessandra Pereyra
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Enrico Massimetti
- UFSMA Val di Cornia, Azienda USL Toscana Nord Ovest, 54100 Massa, Italy;
| | - Ivan Mirko Cremone
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Stefano Pini
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
| | - Barbara Carpita
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy; (L.D.); (C.B.); (G.A.); (M.A.P.); (I.M.C.); (S.P.); (B.C.)
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7
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Lefebvre A, Traut N, Pedoux A, Maruani A, Beggiato A, Elmaleh M, Germanaud D, Amestoy A, Ly-Le Moal M, Chatham C, Murtagh L, Bouvard M, Alisson M, Leboyer M, Bourgeron T, Toro R, Dumas G, Moreau C, Delorme R. Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications. Mol Autism 2023; 14:45. [PMID: 38012709 PMCID: PMC10680239 DOI: 10.1186/s13229-023-00576-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Repetitive and restricted behaviors and interests (RRBI) are core symptoms of autism with a complex entity and are commonly categorized into 'motor-driven' and 'cognitively driven'. RRBI symptomatology depends on the individual's clinical environment limiting the understanding of RRBI physiology, particularly their associated neuroanatomical structures. The complex RRBI heterogeneity needs to explore the whole RRBI spectrum by integrating the clinical context [autistic individuals, their relatives and typical developing (TD) individuals]. We hypothesized that different RRBI dimensions would emerge by exploring the whole spectrum of RRBI and that these dimensions are associated with neuroanatomical signatures-involving cortical and subcortical areas. METHOD A sample of 792 individuals composed of 267 autistic subjects, their 370 first-degree relatives and 155 TD individuals was enrolled in the study. We assessed the whole patterns of RRBI in each individual by using the Repetitive Behavior Scale-Revised and the Yale-Brown Obsessive Compulsive Scale. We estimated brain volumes using MRI scanner for a subsample of the subjects (n = 152, 42 ASD, 89 relatives and 13 TD). We first investigated the dimensionality of RRBI by performing a principal component analysis on all items of these scales and included all the sampling population. We then explored the relationship between RRBI-derived factors with brain volumes using linear regression models. RESULTS We identified 3 main factors (with 30.3% of the RRBI cumulative variance): Factor 1 (FA1, 12.7%) reflected mainly the 'motor-driven' RRBI symptoms; Factor 2 and 3 (respectively, 8.8% and 7.9%) gathered mainly Y-BOCS related items and represented the 'cognitively driven' RRBI symptoms. These three factors were significantly associated with the right/left putamen volumes but with opposite effects: FA1 was negatively associated with an increased volume of the right/left putamen conversely to FA2 and FA3 (all uncorrected p < 0.05). FA1 was negatively associated with the left amygdala (uncorrected p < 0.05), and FA2 was positively associated with the left parietal structure (uncorrected p = 0.001). CONCLUSION Our results suggested 3 coherent RRBI dimensions involving the putamen commonly and other structures according to the RRBI dimension. The exploration of the putamen's integrative role in RSBI needs to be strengthened in further studies.
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Affiliation(s)
- Aline Lefebvre
- Fondation Vallée, GHT Paris Sud, Hospital of Child and Adolescent Psychiatry, Gentilly, France.
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France.
- UNIACT Neurospin - INSERM UMR 1129, CEA, Saclay, France.
- Department of Adult Psychiatry, Henri Mondor and Albert Chenevier Hospital, Créteil, France.
- Faculty of Medicine, Université Paris-Saclay, Le Kremlin-Bicêtre, France.
| | - Nicolas Traut
- Unité de Neuroanatomie Appliquée et Théorique, Institut Pasteur, Paris, France
| | - Amandine Pedoux
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Anna Maruani
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Anita Beggiato
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Monique Elmaleh
- Department of Pediatric Radiology, Robert-Debré Hospital, APHP, Paris, France
| | - David Germanaud
- UNIACT Neurospin - INSERM UMR 1129, CEA, Saclay, France
- Department of Clinical Genetics, Robert Debré Hospital, APHP, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Cité, Paris, France
| | - Anouck Amestoy
- Autism Expert Center, Charles Perrens Hospital, Bordeaux, France
- Fondation FondaMental, French National Science Foundation, Créteil, France
| | | | - Christopher Chatham
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Lorraine Murtagh
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Manuel Bouvard
- Autism Expert Center, Charles Perrens Hospital, Bordeaux, France
- Fondation FondaMental, French National Science Foundation, Créteil, France
| | - Marianne Alisson
- Department of Pediatric Radiology, Robert-Debré Hospital, APHP, Paris, France
| | - Marion Leboyer
- Fondation FondaMental, French National Science Foundation, Créteil, France
- Institut National de la Santé et de la Recherche Médicale (INSERM), U955, Institut Mondor de Recherche Biomédicale, Psychiatrie Translationnelle, Créteil, France
| | - Thomas Bourgeron
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Université Paris Cité, Paris, France
| | - Roberto Toro
- Unité de Neuroanatomie Appliquée et Théorique, Institut Pasteur, Paris, France
| | - Guillaume Dumas
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, QC, Canada
| | - Clara Moreau
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Richard Delorme
- Fondation Vallée, GHT Paris Sud, Hospital of Child and Adolescent Psychiatry, Gentilly, France
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Fondation FondaMental, French National Science Foundation, Créteil, France
- Université Paris Cité, Paris, France
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8
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Montazeri F, Buitelaar JK, Oosterling IJ, de Bildt A, Anderson GM. Network Structure of Autism Spectrum Disorder Behaviors and Its Evolution in Preschool Children: Insights from a New Longitudinal Network Analysis Method. J Autism Dev Disord 2023; 53:4293-4307. [PMID: 36066728 DOI: 10.1007/s10803-022-05723-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2022] [Indexed: 11/30/2022]
Abstract
Network modeling of the social, communication and restrictive/repetitive behaviors (RRBs) included in the definition of Autism Spectrum Disorder was performed. The Autism Diagnostic Interview-Revised (ADI-R) assessed behaviors in 139 pre-school cases at two cross-sections that averaged 34.8 months apart. Cross-sectional networks were based on the correlation matrix of the ADI-R behavioral items and the "bootCross" method was developed and enabled the estimation of a longitudinal network. At both stages, RRB items/nodes formed a consistent peripheral cluster, while social and communication nodes formed a core cluster that diverged with time. These differences in the nature and evolution of the RRB and socio-communicative dimensions indicate that their inter-behavior dynamics are very different. The most central behaviors across stages are proposed as prime targets for efficient therapeutic intervention.
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Affiliation(s)
- Farhad Montazeri
- Child Study Center, Yale University School of Medicine, 230 S. Frontage Rd, New Haven, CT, USA.
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboudumc, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Iris J Oosterling
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Annelies de Bildt
- Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, Lübeckweg 2, NL-9723 HE, Groningen, The Netherlands
- Accare, Child Study Center, Groningen, The Netherlands
| | - George M Anderson
- Child Study Center, Yale University School of Medicine, 230 S. Frontage Rd, New Haven, CT, USA
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9
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Starr J, Falk CF. Comparison of latent variable and psychological network models in PROMIS data: output metrics and factor structure. Qual Life Res 2023; 32:3247-3255. [PMID: 37420022 DOI: 10.1007/s11136-023-03471-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/23/2023] [Indexed: 07/09/2023]
Abstract
PURPOSE Much research is still needed to compare traditional latent variable models such as confirmatory factor analysis (CFA) to emerging psychometric models such as the Gaussian graphical model (GGM). Previous comparisons of GGM centrality indices with factor loadings from CFA have discovered redundancies, and investigations into how well a GGM-based alternative to exploratory factor analysis (i.e., exploratory graph analysis, or EGA) is able to recover the hypothesized factor structure show mixed results. Importantly, such comparisons have not typically been examined in real mental and physical health symptom data, despite such data being an excellent candidate for the GGM. Our goal was to extend previous work by comparing the GGM and CFA using data from Wave 1 of the Patient Reported Outcomes Measurement Information System (PROMIS). METHODS Models were fit to PROMIS data based on 16 test forms designed to measure 9 mental and physical health domains. Our analyses borrowed a two-stage approach for handling missing data from the structural equation modeling literature. RESULTS We found weaker correspondence between centrality indices and factor loadings than found by previous research, but in a similar pattern of correspondence. EGA recommended a factor structure discrepant with PROMIS domains in most cases yet may be taken to provide substantive insight into the dimensionality of PROMIS domains. CONCLUSION In real mental and physical health data, the GGM and EGA may provide complementary information to traditional CFA metrics.
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Affiliation(s)
- Joshua Starr
- Department of Psychology, McGill University, 2001 McGill College Ave., 7th Floor, Montreal, QC, H3A 1G1, Canada
| | - Carl F Falk
- Department of Psychology, McGill University, 2001 McGill College Ave., 7th Floor, Montreal, QC, H3A 1G1, Canada.
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10
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Coughlan B, Woolgar M, van IJzendoorn MH, Duschinsky R. Socioemotional profiles of autism spectrum disorders, attention deficit hyperactivity disorder, and disinhibited and reactive attachment disorders: a symptom comparison and network approach. Dev Psychopathol 2023; 35:1026-1035. [PMID: 34766900 DOI: 10.1017/s0954579421000882] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Children with autism spectrum disorders (ASDs), attention deficit hyperactivity disorder (ADHD) and disinhibited and reactive attachment disorders (RAD/DAD) often experience socioemotional problems. Elucidating a clear picture of these profiles is essential. Strengths and Difficulties Questionnaires (SDQs) were analysed from cohort of children with ASD (n = 1430), ADHD (n = 1193), and RAD/DAD (n = 39). Kruskal-Wallis Tests and network analytic techniques were used to investigate symptom profiles. Children with ASD experienced more emotional problems, peer problems and fewer prosocial behaviours. Children with ADHD and RAD/DAD had higher levels of hyperactivity and conduct problems. Overall, ASD and ADHD networks were highly correlated (rs = 0.82), and we did not observe a statistically significant difference in terms of global Strength.
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Affiliation(s)
- Barry Coughlan
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Matt Woolgar
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Marinus H van IJzendoorn
- Department of Psychology, Education, and Child Studies, Erasmus University Rotterdam, Rotterdam, Netherlands
- Research Department of Clinical, Educational and Health Psychology, Division on Psychology and Language Sciences, Faculty of Brain Sciences, UCL, London, UK
| | - Robbie Duschinsky
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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11
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Leoni M, Vanes LD, Hadaya L, Kanel D, Dazzan P, Simonoff E, Counsell SJ, Happé F, Edwards AD, Nosarti C. Exploring cognitive, behavioral and autistic trait network topology in very preterm and term-born children. Front Psychol 2023; 14:1119196. [PMID: 37187563 PMCID: PMC10176608 DOI: 10.3389/fpsyg.2023.1119196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/30/2023] [Indexed: 05/17/2023] Open
Abstract
Introduction Compared to full-term (FT) born peers, children who were born very preterm (VPT; <32 weeks' gestation) are likely to display more cognitive and behavioral difficulties, including inattention, anxiety and socio-communication problems. In the published literature, such difficulties tend to be studied independently, thus failing to account for how different aspects of child development interact. The current study aimed to investigate children's cognitive and behavioral outcomes as interconnected, dynamically related facets of development that influence one another. Methods Participants were 93 VPT and 55 FT children (median age 8.79 years). IQ was evaluated with the Wechsler Intelligence Scale for Children-4th edition (WISC-IV), autism spectrum condition (ASC) traits with the social responsiveness scale-2nd edition (SRS-2), behavioral and emotional problems with the strengths and difficulties questionnaire (SDQ), temperament with the temperament in middle childhood questionnaire (TMCQ) and executive function with the behavior rating inventory of executive functioning (BRIEF-2). Outcome measures were studied in VPT and FT children using Network Analysis, a method that graphically represents partial correlations between variables and yields information on each variable's propensity to form a bridge between other variables. Results VPT and FT children exhibited marked topological differences. Bridges (i.e., the variables most connected to others) in the VPT group network were: conduct problems and difficulties with organizing and ordering their environment. In the FT group network, the most important bridges were: difficulties with initiating a task or activity and prosocial behaviors, and greater emotional problems, such as lower mood. Discussion These findings highlight the importance of targeting different aspects of development to support VPT and FT children in person-based interventions.
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Affiliation(s)
- Marguerite Leoni
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Lucy D. Vanes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Laila Hadaya
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Dana Kanel
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust and King's College London, National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre, London, United Kingdom
| | - Emily Simonoff
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
- South London and Maudsley NHS Foundation Trust and King's College London, National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre, London, United Kingdom
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Francesca Happé
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - A. David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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12
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Vandewouw MM, Brian J, Crosbie J, Schachar RJ, Iaboni A, Georgiades S, Nicolson R, Kelley E, Ayub M, Jones J, Taylor MJ, Lerch JP, Anagnostou E, Kushki A. Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data. JAMA Netw Open 2023; 6:e232066. [PMID: 36912839 PMCID: PMC10011941 DOI: 10.1001/jamanetworkopen.2023.2066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/14/2023] Open
Abstract
IMPORTANCE Neurodevelopmental conditions, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have highly heterogeneous and overlapping phenotypes and neurobiology. Data-driven approaches are beginning to identify homogeneous transdiagnostic subgroups of children; however, findings have yet to be replicated in independently collected data sets, a necessity for translation into clinical settings. OBJECTIVE To identify subgroups of children with and without neurodevelopmental conditions with shared functional brain characteristics using data from 2 large, independent data sets. DESIGN, SETTING, AND PARTICIPANTS This case-control study used data from the Province of Ontario Neurodevelopmental (POND) network (study recruitment began June 2012 and is ongoing; data were extracted April 2021) and the Healthy Brain Network (HBN; study recruitment began May 2015 and is ongoing; data were extracted November 2020). POND and HBN data are collected from institutions across Ontario and New York, respectively. Participants who had diagnoses of ASD, ADHD, and OCD or were typically developing (TD); were aged between 5 and 19 years; and successfully completed the resting-state and anatomical neuroimaging protocol were included in the current study. MAIN OUTCOMES AND MEASURES The analyses consisted of a data-driven clustering procedure on measures derived from each participant's resting-state functional connectome, performed independently on each data set. Differences between each pair of leaves in the resulting clustering decision trees in the demographic and clinical characteristics were tested. RESULTS Overall, 551 children and adolescents were included from each data set. POND included 164 participants with ADHD; 217 with ASD; 60 with OCD; and 110 with TD (median [IQR] age, 11.87 [9.51-14.76] years; 393 [71.2%] male participants; 20 [3.6%] Black, 28 [5.1%] Latino, and 299 [54.2%] White participants) and HBN included 374 participants with ADHD; 66 with ASD; 11 with OCD; and 100 with TD (median [IQR] age, 11.50 [9.22-14.20] years; 390 [70.8%] male participants; 82 [14.9%] Black, 57 [10.3%] Hispanic, and 257 [46.6%] White participants). In both data sets, subgroups with similar biology that differed significantly in intelligence as well as hyperactivity and impulsivity problems were identified, yet these groups showed no consistent alignment with current diagnostic categories. For example, there was a significant difference in Strengths and Weaknesses ADHD Symptoms and Normal Behavior Hyperactivity/Impulsivity subscale (SWAN-HI) between 2 subgroups in the POND data (C and D), with subgroup D having increased hyperactivity and impulsivity traits compared with subgroup C (median [IQR], 2.50 [0.00-7.00] vs 1.00 [0.00-5.00]; U = 1.19 × 104; P = .01; η2 = 0.02). A significant difference in SWAN-HI scores between subgroups g and d in the HBN data was also observed (median [IQR], 1.00 [0.00-4.00] vs 0.00 [0.00-2.00]; corrected P = .02). There were no differences in the proportion of each diagnosis between the subgroups in either data set. CONCLUSIONS AND RELEVANCE The findings of this study suggest that homogeneity in the neurobiology of neurodevelopmental conditions transcends diagnostic boundaries and is instead associated with behavioral characteristics. This work takes an important step toward translating neurobiological subgroups into clinical settings by being the first to replicate our findings in independently collected data sets.
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Affiliation(s)
- Marlee M. Vandewouw
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Jessica Brian
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer Crosbie
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Russell J. Schachar
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Alana Iaboni
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
| | - Stelios Georgiades
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Robert Nicolson
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Elizabeth Kelley
- Department of Psychology, Queen’s University, Kingston, Ontario, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario, Canada
- Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
| | - Muhammad Ayub
- Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
| | - Jessica Jones
- Department of Psychology, Queen’s University, Kingston, Ontario, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, Ontario, Canada
- Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
| | - Margot J. Taylor
- Program in Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Jason P. Lerch
- Program in Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Evdokia Anagnostou
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Program in Neurosciences & Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Azadeh Kushki
- Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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13
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Gupta R, Mehan S, Chhabra S, Giri A, Sherawat K. Role of Sonic Hedgehog Signaling Activation in the Prevention of Neurological Abnormalities Associated with Obsessive-Compulsive Disorder. Neurotox Res 2022; 40:1718-1738. [PMID: 36272053 DOI: 10.1007/s12640-022-00586-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 09/15/2022] [Accepted: 10/07/2022] [Indexed: 12/31/2022]
Abstract
The smoothened sonic hedgehog (Smo-Shh) pathway is one mechanism that influences neurogenesis, including brain cell differentiation and development during childhood. Shh signaling dysregulation leads to decreased target gene transcription, which contributes to increased neuronal excitation, apoptosis, and neurodegeneration, eventually leading to neurological deficits. Neuropsychiatric disorders such as OCD and related neurological dysfunctions are characterized by neurotransmitter imbalance, neuroinflammation, oxidative stress, and impaired neurogenesis, disturbing the cortico-striato-thalamo-cortical (CSTC) link neuronal network. Despite the availability of several treatments, such as selective serotonin reuptake inhibitors, some individuals may not benefit much from them. Several trials on the use of antipsychotics in the treatment of OCD have also produced inadequate findings. This evidence-based review focuses on a potential pharmacological approach to alleviating OCD and associated neuronal deficits by preventing neurochemical alterations, in which sonic hedgehog activators are neuroprotective, lowering neuronal damage while increasing neuronal maintenance and survival. As a result, stimulating SMO-Shh via its potential activators may have neuroprotective effects on neurological impairment associated with OCD. This review investigates the link between SMO-Shh signaling and the neurochemical abnormalities associated with the progression of OCD and associated neurological dysfunctions. Role of Smo-Shh signaling in serotonergic neurogenesis and in maintaining their neuronal identity. The Shh ligand activates two main transcriptional factors known as Foxa2 and Nkx2.2, which again activates another transcriptional factor, GATA (GATA2 and GATA3), in post mitotic precursor cells of serotonergic neurons-following increased expression of Pet-1 and Lmx1b after GATA regulates the expression of many serotonergic enzymes such as TPH2, SERT, VMAT, slc6a4, Htr1a, Htr1b (Serotonin receptor enzymes), and MAO that regulate and control the release of serotonin and maintain their neuronal identity after their maturation. Abbreviation: Foxa2: Forkhead box; GATA: Globin transcription factor; Lmx1b: LIM homeobox transcription factor 1 beta; TPH2: Tryptophan hydroxylase 2; Htr1a: Serotonin receptor 1a; Htr1b: Serotonin receptor 1b; SERT: Serotonin transporter; VMAT: Vesicular monoamine transporter; MAO: Monoamine oxidase.
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Affiliation(s)
- Ria Gupta
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India
| | - Sidharth Mehan
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India.
| | - Swesha Chhabra
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India
| | - Aditi Giri
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India
| | - Kajal Sherawat
- Division of Neuroscience, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India
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14
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Mukherjee R, Halder S. Students with autism in an alternative classroom during COVID-19 pandemic: experiences shared by special educators in India. INTERNATIONAL JOURNAL OF DEVELOPMENTAL DISABILITIES 2022; 70:696-710. [PMID: 38983496 PMCID: PMC11229772 DOI: 10.1080/20473869.2022.2137957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 10/14/2022] [Indexed: 07/11/2024]
Abstract
Introduction: During the COVID-19 pandemic, the students with Autism faced difficulties in teaching-learning due to campus closures. The special schools opted for alternative classrooms i.e. online mode. Due to certain specific and unique characteristics, the learning experiences of students with autism would be different from neurotypical students. Objectives: To know about the challenges and facilitators of the alternative classroom through the teacher's narratives. Method: The virtual interviews recorded by 15 special educators from special schools in Kolkata city and its outskirts, selected using purposive sampling were analyzed through inductive thematic analysis. Results: The generated themes reveal the challenges of setting up and adapting to the online classes faced by special educators, students, and their parents. The study findings also inform about the advantages gained during the pandemic such as parental involvement for better learning in a safe space. Conclusion: A combined mode of teaching might be appropriate for the future to bring out the best in the learners.
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Affiliation(s)
| | - Santoshi Halder
- Department of Education, University of Calcutta, Kolkata, India
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15
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Lachance K, Štětinová K, Rieske R, Peer S. Repetitive Behavior Scale for Early Childhood (RBS-EC): Psychometrics and Developmental Effects with a Community Sample. Child Psychiatry Hum Dev 2022; 53:863-875. [PMID: 33871734 DOI: 10.1007/s10578-021-01166-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/30/2021] [Indexed: 11/30/2022]
Abstract
Restricted, repetitive behaviors and interests (RRBIs) occur commonly in young children in the course of typical development, but too frequent or persistent RRBIs have been linked to a variety of psychosocial and neurodevelopmental disorders. Unfortunately, a lack of psychometrically sound, feasible instruments stymies RRBI study and intervention in early childhood. Therefore, this study validated an extant RRBI measure (i.e., Repetitive Behavior Scale for Early Childhood; RBS-EC) for predominately neurotypical community children ages 2-7 years via an MTurk survey of 300 caregivers. Confirmatory factor analyses best supported a 4-factor model for the RBS-EC (i.e., repetitive motor, rituals and routines, restricted interests, self-directed behaviors). RBS-EC scores varied significantly with age and gender; namely, RRBIs were typically (1) less frequent but more problematic with older versus younger children and (2) more frequent and problematic with boys versus girls. Findings extend the RBS-EC's utility in RRBI assessment and treatment during early childhood.
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Affiliation(s)
- Kathryn Lachance
- Department of Psychology, Idaho State University, 921 S 8th Ave STOP 8201, Pocatello, ID, 83209, USA
| | - Karolina Štětinová
- Department of Psychology, Idaho State University, 921 S 8th Ave STOP 8201, Pocatello, ID, 83209, USA
| | - Robert Rieske
- Department of Psychology, Idaho State University, 921 S 8th Ave STOP 8201, Pocatello, ID, 83209, USA.
| | - Samuel Peer
- Department of Psychology, Idaho State University, 921 S 8th Ave STOP 8201, Pocatello, ID, 83209, USA
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16
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Verhulst I, MacLennan K, Haffey A, Tavassoli T. The Perceived Causal Relations Between Sensory Reactivity Differences and Anxiety Symptoms in Autistic Adults. AUTISM IN ADULTHOOD 2022; 4:183-192. [PMID: 36606154 PMCID: PMC9648696 DOI: 10.1089/aut.2022.0018] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Background Rates of anxiety are inordinately high in autistic adults. Sensory reactivity differences, such as hyperreactivity (e.g., strong reactions to sound), hyporeactivity (e.g., no, or slower reactions to pain), and seeking (e.g., fascination with spinning objects), are a diagnostic criterion of autism and have been linked with anxiety. Understanding how individuals perceive these to be causally related can impact the assessment and treatment of anxiety. Therefore, we examined the perceived causal relations (PCR) between sensory reactivity differences and anxiety in autistic adults. Method Two hundred forty-six autistic adults aged 18-76 years took part in an online study. They completed self-report assessments of sensory reactivity differences, and anxiety, followed by the PCR scale, indicating whether they perceived their sensory reactivity differences to be more of a cause or an effect of their anxiety symptoms. Results We found sensory reactivity hyperreactivity, hyporeactivity, and seeking to be significantly correlated with anxiety. Further, we found total sensory hyperreactivity, and visual, auditory, and olfactory hyperreactivity, to be perceived as significantly more of a cause of anxiety than an effect, and total sensory seeking, and tactile and vestibular seeking, to be perceived as significantly more of an effect of anxiety than a cause. Conclusion Future individualized approaches to treating anxiety in autistic individuals may benefit from differentiating between potential sensory causes of anxiety (e.g. hypersensitivities) vs. potential sensory effects of anxiety (e.g. sensory seeking behaviors).
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Affiliation(s)
- Isabelle Verhulst
- Department of Psychology, Royal Holloway, University of London, Egham, United Kingdom
| | - Keren MacLennan
- School of Psychology and Clinical Language Sciences, The University of Reading, Berkshire, United Kingdom
| | - Anthony Haffey
- School of Psychology and Clinical Language Sciences, The University of Reading, Berkshire, United Kingdom
| | - Teresa Tavassoli
- School of Psychology and Clinical Language Sciences, The University of Reading, Berkshire, United Kingdom
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17
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Ferreira F, Gysi D, Castro D, Ferreira TB. The nosographic structure of posttraumatic stress symptoms across trauma types: An exploratory network analysis approach. J Trauma Stress 2022; 35:1115-1128. [PMID: 35246860 DOI: 10.1002/jts.22818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/06/2021] [Accepted: 01/11/2022] [Indexed: 11/12/2022]
Abstract
The nosographic structure of posttraumatic stress disorder (PTSD) remains unclear, and attempts to determine its symptomatic organization have been unsatisfactory. Several explanations have been suggested, and the impact of trauma type is receiving increasing attention. As little is known about the differential impact trauma type in the nosographic structure of PTSD, we explored the nosology of PTSD and the effect of trauma type on its symptomatic organization. We reanalyzed five cross-sectional psychopathological networks involving different trauma types, encompassing a broad range of traumatic events in veterans, war-related trauma in veterans, sexual abuse, terrorist attacks, and various traumatic events in refugees. The weighted topological overlap was used to estimate the networks and attribute weights to their links. Coexpression differential network analysis was used to identify the common and specific network structures of the connections across different trauma types and to determine the importance of symptoms across the networks. We found a set of symptoms with more common connections with other symptoms, suggesting that these might constitute the prototypical nosographic structure of PTSD. We also found a set of symptoms that had a high number of specific connections with other symptoms; these connections varied according to trauma type. The importance of symptoms across the common and specific networks was ascertained. The present findings offer new insights into the symptomatic organization of PTSD and support previous research on the impact of trauma type on the nosology of this disorder.
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Affiliation(s)
- Filipa Ferreira
- Social Sciences Department, University Institute of Maia, Maia, Portugal.,Centre for Psychology at University of Porto, Porto, Portugal
| | - Deisy Gysi
- Center for Complex Network Research, Northeastern University, Boston, Massachusetts, USA
| | - Daniel Castro
- Social Sciences Department, University Institute of Maia, Maia, Portugal.,Centre for Psychology at University of Porto, Porto, Portugal
| | - Tiago Bento Ferreira
- Social Sciences Department, University Institute of Maia, Maia, Portugal.,Centre for Psychology at University of Porto, Porto, Portugal
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Marsman M, Rhemtulla M. Guest Editors' Introduction to The Special Issue "Network Psychometrics in Action": Methodological Innovations Inspired by Empirical Problems. PSYCHOMETRIKA 2022; 87:1-11. [PMID: 35397084 PMCID: PMC9021145 DOI: 10.1007/s11336-022-09861-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 01/28/2022] [Indexed: 06/14/2023]
Affiliation(s)
- Maarten Marsman
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
- University of Amsterdam, Psychological Methods, Nieuwe Achtergracht 129B, PO Box 15906, 1001 NK, Amsterdam, The Netherlands.
| | - Mijke Rhemtulla
- Department of Psychology, University of California at Davis, Davis, California, USA
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19
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Hofer J, Tillmann J, Salzmann J, Bölte S, Fellinger J, Holzinger D. Screening for autism spectrum disorder in deaf adults with intellectual disability: Feasibility and accuracy of two autism screening instruments. RESEARCH IN DEVELOPMENTAL DISABILITIES 2022; 122:104167. [PMID: 34998116 DOI: 10.1016/j.ridd.2021.104167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/22/2021] [Accepted: 12/28/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND There is a lack of autism screening instruments for deaf or hard of hearing (DHH) adults with intellectual disability. AIMS This study examined the diagnostic validity of the Pervasive Developmental Disorder in Mental Retardation Scale and the Diagnostic Behavioral Assessment for autism spectrum disorder - Revised in this rare population. METHODS AND PARTICIPANTS 56 DHH adults with intellectual disability living in three specialized therapeutic communities were examined, 9 of whom met criteria for autism. OUTCOMES AND RESULTS With minimal adaptions regarding item interpretation, both tools showed good diagnostic and high convergent validity. Items probing for difficulties in reciprocal social interaction and restricted interests were discriminant between individuals with and without autism. CONCLUSION These data suggest that both autism screening tools are feasible and psychometrically sound when used with appropriate adaptations for DHH adults with intellectual disability.
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Affiliation(s)
- J Hofer
- Research Institute for Developmental Medicine, Johannes Kepler University, Linz, Austria; Institute of Neurology of Language and Senses, Hospital of St. John of God, Linz, Austria; Department of Pediatrics I, Medical University of Innsbruck, Austria
| | - J Tillmann
- Research Institute for Developmental Medicine, Johannes Kepler University, Linz, Austria
| | - J Salzmann
- Institute of Neurology of Language and Senses, Hospital of St. John of God, Linz, Austria
| | - S Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden; Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden; Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, Western Australia, Australia
| | - J Fellinger
- Research Institute for Developmental Medicine, Johannes Kepler University, Linz, Austria; Institute of Neurology of Language and Senses, Hospital of St. John of God, Linz, Austria; Division of Social Psychiatry, University Clinic for Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - D Holzinger
- Research Institute for Developmental Medicine, Johannes Kepler University, Linz, Austria; Institute of Neurology of Language and Senses, Hospital of St. John of God, Linz, Austria; Institute of Linguistics, University of Graz, Graz, Austria.
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20
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Dingemans AE, Volkmer SA, Mulkens S, Vuijk R, van Rood YR. The obsessive-compulsive spectrum: A network analysis. Psychiatry Res 2022; 308:114351. [PMID: 34979379 DOI: 10.1016/j.psychres.2021.114351] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 12/17/2021] [Accepted: 12/18/2021] [Indexed: 11/24/2022]
Abstract
Several studies have shown that obsessive-compulsive disorder (OCD), eating disorders (ED), autism spectrum disorders (ASD) and body dysmorphic disorder (BDD) share obsessive-compulsive (OC) symptoms and often co-occur, which could be seen as indicative of a common etiological basis. In addition, they also appear to have similarities in executive functioning. The present study investigated disorder-specific symptoms and executive functioning as a possible joint factor in individuals with OCD (n=53), BDD (n=95), ED (n=171) and ASD (n=73), and in healthy controls (n=110). The participants completed online questionnaires measuring OCD, ED, ASD and BDD related symptoms as well as executive functioning. The clinical groups were first compared to the healthy controls. Subsequently, a network analysis was performed only with the OC-groups. This network approach assumes that psychopathological disorders are the result of causal symptom interactions. As expected, the healthy controls reported less severe symptoms compared to the OC patient groups. The network analysis suggested that the executive functioning skill set shifting/attention switching and the ASD symptoms, social and communication skills were the most central nodes in the model. Difficulty with cognitive flexibility and social factors are central in OC-spectrum disorders and may be perpetuating factors and thus a relevant focus of treatment.
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Affiliation(s)
| | | | - Sandra Mulkens
- Department of Psychiatry and Neuropsychology, and Department of Clinical Psychological Science, Maastricht University, Maastricht, The Netherlands
| | | | - Yanda R van Rood
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
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21
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Farhat LC, Brentani H, de Toledo VHC, Shephard E, Mattos P, Baron-Cohen S, Thapar A, Casella E, Polanczyk GV. ADHD and autism symptoms in youth: a network analysis. J Child Psychol Psychiatry 2022; 63:143-151. [PMID: 33984874 DOI: 10.1111/jcpp.13436] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/30/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Previous research investigating the overlap between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (henceforth, autism) symptoms in population samples have relied on latent variable modeling in which averaged scores representing dimensions were derived from observed symptoms. There are no studies evaluating how ADHD and autism symptoms interact at the level of individual symptom items. METHODS We aimed to address this gap by performing a network analysis on data from a school survey of children aged 6-17 years old (N = 7,405). ADHD and autism symptoms were measured via parent-report on the Swanson, Nolan, Pelham-IV questionnaire and the Childhood Autism Spectrum test, respectively. RESULTS A relatively low interconnectivity between ADHD and autism symptoms was found with only 10.06% of possible connections (edges) between one ADHD and one autism symptoms different than zero. Associations between ADHD and autism symptoms were significantly weaker than those between two symptoms pertaining to the same construct. Select ADHD symptoms, particularly those presenting in social contexts (e.g. 'talks excessively', 'does not wait turn'), showed moderate-to-strong associations with autism symptoms, but some were considered redundant to autism symptoms. CONCLUSIONS The present findings indicate that individual ADHD and autism symptoms are largely segregated in accordance with diagnostic boundaries corresponding to these conditions in children and adolescents from the community. These findings could improve our clinical conceptualization of ADHD and autism and guide advancements in diagnosis and treatment.
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Affiliation(s)
- Luis C Farhat
- Departamento de Psiquiatria da Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Helena Brentani
- Departamento de Psiquiatria da Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | | | - Elizabeth Shephard
- Departamento de Psiquiatria da Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK
| | - Paulo Mattos
- Institute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Simon Baron-Cohen
- Department of Psychiatry, Autism Research Center, University of Cambridge, Cambridge, UK
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, Medical Research Council Center for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | - Erasmo Casella
- Instituto da Criança, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Guilherme V Polanczyk
- Departamento de Psiquiatria da Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
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22
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Berta A, Miguel Ángel C, Clara GS, Rubén H. A bibliometric analysis of 10 years of research on symptom networks in psychopathology and mental health. Psychiatry Res 2022; 308:114380. [PMID: 34999293 DOI: 10.1016/j.psychres.2021.114380] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 12/21/2021] [Accepted: 12/29/2021] [Indexed: 11/18/2022]
Abstract
Psychopathology networks consist of aspects (e.g., symptoms) of mental disorders (nodes) and the connections between those aspects (edges). This article aims to analyze the research literature on network analysis in psychopathology and mental health for the last ten years. Statistical descriptive analysis was complemented with two bibliometric techniques: performance analysis and co-word analysis. There is an increase in publications that has passed from 1 article published in 2010 to 172 papers published in 2020. The 398 articles in the sample have 1,910 authors in total, being most of them occasional contributors. The Journal of Affective Disorders is the one with the highest number of publications on network analysis in psychopathology and mental health, followed by the Journal of Abnormal Psychology and Psychological Medicine stand out. The present study shows that this perspective in psychopathology and mental health is a recent field of study, but with solid advances in recent years from a wide variety of researchers, mainly from USA and Europe, who have extensively studied symptom networks in depression, anxiety, and post-traumatic stress disorders. However, gaps are identified in other psychological behaviors such as suicide, populations such as the elderly, and gender studies.
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Affiliation(s)
- Ausín Berta
- School of Psychology, Personality, Evaluation and Clinical Psychology Department, Complutense University of Madrid, Spain.
| | - Castellanos Miguel Ángel
- School of Psychology, Psychobiology and Methodology in Behavioral Sciences Department, Complutense University of Madrid, Spain
| | - González-Sanguino Clara
- School of Psychology, Personality, Evaluation and Clinical Psychology Department, Complutense University of Madrid, Spain
| | - Heradio Rubén
- Department of Computer Systems and Software Engineering, National Distance Education University, Madrid, Spain
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23
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Brown SL, Marshall AJ, Mitchell SM, Roush JF, Mumma GH, Jahn DR, Ribeiro JD, Joiner TE, Cukrowicz KC. Suicide Ideation and Thwarted Interpersonal Needs among Psychiatric Inpatients: A Network Approach. Clin Psychol Sci 2022; 9:1080-1094. [PMID: 35070498 DOI: 10.1177/21677026211000670] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
We aimed to demonstrate the utility of an item-level network analysis approach to suicide risk by testing the interpersonal psychological theory of suicide (IPTS) among 402 psychiatric inpatients. We hypothesized specific thwarted belongingness (TB) or perceived burdensomeness (PB; Interpersonal Needs Questionnaire items) facets would positively relate to passive or active suicide ideation, and these facets would positively relate to each other and form distinct clusters. We also tested TB and PB facets central to the networks as predictors of suicide ideation compared to the full TB and PB subscales. Face-valid items congruent with latent constructs proposed by the IPTS (i.e., feelings of burden on society, feeling that one does not belong) were the only two facets uniquely predictive of passive and active suicide ideation. Facets of TB and PB did not form distinct clusters. Item-level network analysis may have important conceptual, assessment, predictive, and clinical implications for understanding suicide risk.
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Affiliation(s)
- Sarah L Brown
- Department of Psychological Sciences, Mail Stop 2051, Texas Tech University, Lubbock, TX 79409-2051
| | - Andrew J Marshall
- Department of Psychological Sciences, Mail Stop 2051, Texas Tech University, Lubbock, TX 79409-2051.,Department of Family & Protective Services, State of Texas, 701 W 51st St, Austin, TX 78751
| | - Sean M Mitchell
- Department of Psychological Sciences, Mail Stop 2051, Texas Tech University, Lubbock, TX 79409-2051.,Department of Psychiatry, University of Rochester Medical Center, 300 Crittenden Blvd., Box Psych, Rochester, NY 14642
| | - Jared F Roush
- Department of Psychological Sciences, Mail Stop 2051, Texas Tech University, Lubbock, TX 79409-2051
| | - Gregory H Mumma
- Department of Psychological Sciences, Mail Stop 2051, Texas Tech University, Lubbock, TX 79409-2051
| | - Danielle R Jahn
- Mental Health Center for Acute Recovery Empowerment, Orlando VA Medical Center, 13800 Veterans Way, Orlando, FL 32827
| | - Jessica D Ribeiro
- Department of Psychology, Florida State University, 1107 W. Call St., Tallahassee, FL 32306
| | - Thomas E Joiner
- Department of Psychology, Florida State University, 1107 W. Call St., Tallahassee, FL 32306
| | - Kelly C Cukrowicz
- Department of Psychological Sciences, Mail Stop 2051, Texas Tech University, Lubbock, TX 79409-2051
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24
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Gossink F, Dols A, Stek ML, Scheltens P, Nijmeijer B, Cohn Hokke P, Dijkstra A, Van Ruissen F, Aalfs C, Pijnenburg YAL. Early life involvement in C9orf72 repeat expansion carriers. J Neurol Neurosurg Psychiatry 2022; 93:93-100. [PMID: 33906932 DOI: 10.1136/jnnp-2020-325994] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 03/12/2021] [Accepted: 04/12/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVES The chromosome 9 open reading frame 72 gene (C9orf72) hexanucleotide repeat expansion (C9orf72RE) is the most common genetic cause of behavioural variant frontotemporal dementia (bvFTD). Since the onset of the C9orf72RE-associated disease is sometimes hard to define, we hypothesise that C9orf72RE may cause a lifelong neuropsychiatric vulnerability. The first aim of our study was to explore lifelong behavioural and personality characteristics in C9orf72RE. Second, we aimed to describe distinctive characteristics of C9orf72RE during disease course. METHODS Out of 183 patients from the Amsterdam Dementia Cohort that underwent genetic testing between 2011 and 2018, 20 C9orf72RE bvFTD patients and 23 C9orf72RE negative bvFTD patients were included. Patients and their relatives were interviewed extensively to chart their biography. Data analysis was performed through a mixed-methods approach including qualitative and quantitative analyses. RESULTS Education, type of professional career and number of intimate partners were not different between carriers and non-carriers. Carriers were more often described by their relatives as having 'fixed behavioural patterns in daily life' and with limited empathy already years before onset of bvFTD symptoms. In carriers, disease course was more often characterised by excessive buying and obsessive physical exercise than in non-carriers. CONCLUSION This is the first study thoroughly exploring biographies of bvFTD patients with C9orf72RE, revealing that subtle personality traits may be present early in life. Our study suggests that C9orf72RE exerts a lifelong neuropsychiatric vulnerability. This may strengthen hypotheses of links between neurodevelopmental and neurodegenerative diseases. Moreover, the presence of a distinct C9orf72RE -associated syndrome within the FTD spectrum opens doors for investigation of vulnerable neuronal networks.
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Affiliation(s)
- Flora Gossink
- Alzheimer Center, Department of Neurology, Location VU University Medical Center, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Annemiek Dols
- Department of Old Age psychiatry, GGZ inGeest Amsterdam locatie De Nieuwe Valerius, Amsterdam, The Netherlands
| | - Max L Stek
- Department of Old Age psychiatry, GGZ inGeest Amsterdam locatie De Nieuwe Valerius, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Location VU University Medical Center, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - Bas Nijmeijer
- Clinical Genetics, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | | | - Anke Dijkstra
- Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | - Fred Van Ruissen
- Department of Clinical Genetics, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
| | | | - Yolande A L Pijnenburg
- Alzheimer Center, Department of Neurology, Location VU University Medical Center, Amsterdam University Medical Centres, Amsterdam, The Netherlands
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25
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Bringmann LF, Albers C, Bockting C, Borsboom D, Ceulemans E, Cramer A, Epskamp S, Eronen MI, Hamaker E, Kuppens P, Lutz W, McNally RJ, Molenaar P, Tio P, Voelkle MC, Wichers M. Psychopathological networks: Theory, methods and practice. Behav Res Ther 2021; 149:104011. [PMID: 34998034 DOI: 10.1016/j.brat.2021.104011] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 11/05/2021] [Accepted: 11/27/2021] [Indexed: 12/19/2022]
Abstract
In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.
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Affiliation(s)
- Laura F Bringmann
- University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), P.O. Box 30.001 (CC72), 9700 RB, Groningen, the Netherlands; University of Groningen, Faculty of Behavioural and Social Sciences, Department of Psychometrics and Statistics, Grote Kruisstraat 2/1, 9712 TS, Groningen, the Netherlands.
| | - Casper Albers
- University of Groningen, Faculty of Behavioural and Social Sciences, Department of Psychometrics and Statistics, Grote Kruisstraat 2/1, 9712 TS, Groningen, the Netherlands
| | - Claudi Bockting
- Centre for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Denny Borsboom
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - Eva Ceulemans
- KU Leuven, Faculty of Psychology and Educational Sciences, Leuven, Belgium
| | - Angélique Cramer
- RIVM National Institute for Public Health and the Environment, the Netherlands
| | - Sacha Epskamp
- Centre for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands; Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - Markus I Eronen
- Department of Theoretical Philosophy, University of Groningen, the Netherlands
| | - Ellen Hamaker
- Department of Methodology and Statistics, Utrecht University, the Netherlands
| | - Peter Kuppens
- KU Leuven, Faculty of Psychology and Educational Sciences, Leuven, Belgium
| | - Wolfgang Lutz
- Department of Psychology, University of Trier, Germany
| | | | - Peter Molenaar
- Department of Human Development and Family Studies, The Pennsylvania State University, USA
| | - Pia Tio
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; Department of Methodology and Statistics, Tilburg University, Tilburg, the Netherlands
| | - Manuel C Voelkle
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Marieke Wichers
- University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), P.O. Box 30.001 (CC72), 9700 RB, Groningen, the Netherlands
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26
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Wang E, Reardon B, Cherian B, George WT, Xavier RM. Disorder agnostic network structure of psychopathology symptoms in youth. J Psychiatr Res 2021; 143:246-253. [PMID: 34509785 DOI: 10.1016/j.jpsychires.2021.09.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 08/26/2021] [Accepted: 09/02/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Youth mental health disorders are strong predictors of adult mental health disorders. Early identification of mental health disorders in youth is important as it could aid early intervention and prevention. In a disorder agnostic manner, we aimed to identify influential psychopathology symptoms that could impact mental health in youth. METHODS This study sampled 6063 participants from the Philadelphia Neurodevelopmental Cohort and comprised of youth of ages 12-21 years. A mixed graphical model was used to estimate the network structure of 115 symptoms corresponding to 16 psychopathology domains. Importance of individual symptoms in the network were assessed using node influence measures such as strength centrality and predictability. RESULTS The generated network had stronger associations between symptoms within a psychopathological domain; overall had no negative associations. A conduct disorder symptom eliciting threatening others and a depression symptom - persistent sadness or depressed mood - had the greatest strength centralities (β = 2.85). Fear of traveling in a car and compulsively going in and out a door had the largest predictability (classification accuracy = 0.99). Conduct disorder, depression, and obsessive compulsive disorder symptoms generally had the largest strength centralities. Suicidal thoughts had the largest bridge strength centrality (β = 2.85). Subgroup networks revealed that network structure differed by socioeconomic status (low versus high, p = 0.04) and network connectivity patterns differed by sex (p = 0.01), but not for age or race. CONCLUSIONS Psychopathology symptom networks offer insights that could be leveraged for early identification, intervention, and possibly prevention of mental health disorders.
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Affiliation(s)
- Emily Wang
- The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brandy Reardon
- The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Benjamin Cherian
- The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wales T George
- Southern Virginia Mental Health Institute, Danville, VA, USA
| | - Rose Mary Xavier
- The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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27
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Smith AR, Hunt RA, Grunewald W, Jeon ME, Stanley IH, Levinson CA, Joiner TE. Identifying Central Symptoms and Bridge Pathways Between Autism Spectrum Disorder Traits and Suicidality Within an Active Duty Sample. Arch Suicide Res 2021; 27:307-322. [PMID: 34689709 DOI: 10.1080/13811118.2021.1993398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
OBJECTIVE This study employed network analysis to characterize central autism spectrum disorder (ASD) traits and suicide symptoms within an active duty military sample as well as to identify symptoms that may bridge between ASD traits and suicidality (i.e., suicidal ideation and behaviors). METHOD Participants were active duty U.S. military service members (N = 287). Autism spectrum traits, suicidality, depression, and suicide related constructs were assessed online via self-report. RESULTS Within the combined ASD trait-suicidality network, suicide rumination, suicide behaviors, and depression had the highest strength centrality. The most central bridge symptoms between ASD and suicidality were thwarted belongingness, social skills deficits, and depressive symptoms. CONCLUSIONS Social skills deficits and thwarted belongingness may function as a meaningful bridge between ASD symptoms and suicidality within active duty members. Individuals with ASD symptoms who additionally present with high levels of thwarted belongingness and/or considerable social skills deficits may be at increased risk for suicidality.HIGHLIGHTSWithin an ASD-suicidality network, social skills deficits, low belonging, and depression had the greatest bridge strength.Although low belonging emerged as a bridge symptom, perceived burdensomeness did not.Suicide rumination, suicide behaviors, and depression were the most central symptom in an ASD-suicidality network.Symptoms related to social skills deficits may connect ASD traits and suicidality.
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28
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Elliott SJ, Marshall D, Morley K, Uphoff E, Kumar M, Meader N. Behavioural and cognitive behavioural therapy for obsessive compulsive disorder (OCD) in individuals with autism spectrum disorder (ASD). Cochrane Database Syst Rev 2021; 9:CD013173. [PMID: 34693989 PMCID: PMC8543671 DOI: 10.1002/14651858.cd013173.pub2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Autistic spectrum disorder (ASD) is an increasingly recognised neurodevelopmental condition; that is, a neurologically-based condition which interferes with the acquisition, retention or application of specific skills. ASD is characterised by challenges with socialisation and communication, and by stereotyped and repetitive behaviours. A stereotyped behaviour is one which is repeated over and over again and which seems not to have any useful function. ASD often co-occurs with mental health disorders, including obsessive compulsive disorder (OCD). People with ASD may show certain cognitive differences (i.e. differences in ways of thinking) which influence their response to therapies. Thus, there is a need for evidence-based guidelines to treat mental health issues in this group. OCD, a common condition characterised by repeated obsessional thoughts and compulsive acts, occurs with greater frequency in persons with ASD than in the general population. Genetic, anatomic, neurobiological and psychological factors have been proposed to explain this co-occurrence. However, care should be taken to distinguish stereotyped and repetitive behaviours characteristic of ASD from obsessive compulsive acts in OCD. Cognitive behavioural therapy (CBT) is the recommended treatment for OCD, but studies have suggested that this treatment may be less effective in those with OCD co-occurring with ASD. Hence, modifications to CBT treatment may be helpful when treating OCD co-occurring with ASD to optimise outcomes. OBJECTIVES To assess the effectiveness of behavioural and cognitive behavioural therapy for obsessive compulsive disorder (OCD) in children and adults with autism spectrum disorder (ASD). SEARCH METHODS We searched for studies in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, PsycINFO, five other bibliographic databases, international trial registries and other sources of grey literature (to 24 August 2020). We checked the reference lists of included studies and relevant systematic reviews to identify additional studies missed from the original electronic searches. We contacted subject experts for further information when needed. SELECTION CRITERIA We included randomised controlled trials (RCTs), cross-over, cluster- and quasi-randomised controlled trials involving both adults and children with diagnoses of OCD and ASD. We included studies of participants with co-occurring conditions (i.e. those experiencing other mental illnesses or neurodevelopmental conditions at the same time), but we did not include individuals who had a co-occurring global learning difficulty. Treatment could be in any setting or format and include behavioural therapy (BT) and cognitive behavioural therapy (CBT), which may have been adapted for those with ASD. Comparator interventions included no treatment, waiting list, attention placebo (where the control group receives non-specific aspects of therapy, but not the active ingredient) and treatment as usual (TAU, where the control group receives the usual treatment, according to accepted standards). DATA COLLECTION AND ANALYSIS Three review authors independently screened studies for inclusion. The authors extracted relevant data from the one eligible study, assessed the risk of bias and certainty of evidence (GRADE). Outcomes of interest were changes in OCD symptoms and treatment completion (primary outcome), and severity of depressive symptoms, anxiety symptoms and behavioural difficulties, as well as degree of family accommodation (secondary outcomes). We did not conduct meta-analyses as only one study met the selection criteria. MAIN RESULTS We included only one RCT of 46 participants in our analysis. This study compared CBT for OCD in persons with high-functioning ASD with a control group who received anxiety management only. There were no differences in rates of treatment completion between the CBT (87%) and anxiety management (87%) groups (risk ratio (RR) 1.00, 95% confidence interval (CI) 0.80 to 1.25; low-certainty evidence). Behavioural difficulties were not included as an outcome measure in the study. This study showed that there may be a benefit at the end of treatment favouring CBT compared with anxiety management in OCD symptoms (mean difference (MD) -3.00, 95% CI -8.02 to 2.02), depression symptoms (MD -1.80, 95% CI -11.50 to 7.90), anxiety symptoms (MD -3.20, 95% CI -11.38 to 4.98), and quality of life (MD 5.20, 95% CI -1.41 to 11.81), but the evidence was of low certainty. AUTHORS' CONCLUSIONS: Evidence is limited regarding the efficacy of CBT for treatment of OCD in ASD. There is much scope for future study, not only examining the efficacy of CBT for OCD in ASD, but also the particular ways that OCD manifests in and affects people with ASD and the role of the family in treatment response.
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Affiliation(s)
- Sarah J Elliott
- Elm House, East Cheshire Child and Adolescent Mental Health Service, Cheshire and Wirral Partnership NHS Foundation Trust, Macclesfield, UK
| | - David Marshall
- Centre for Reviews and Dissemination, University of York, York, UK
- Cochrane Common Mental Disorders, University of York, York, UK
| | | | - Eleonora Uphoff
- Centre for Reviews and Dissemination, University of York, York, UK
- Cochrane Common Mental Disorders, University of York, York, UK
| | - Mrityunjai Kumar
- Wigan Child and Adolescent Mental Health Service, Greater Manchester Mental Health NHS Foundation Trust, Wigan, UK
| | - Nicholas Meader
- Centre for Reviews and Dissemination, University of York, York, UK
- Cochrane Common Mental Disorders, University of York, York, UK
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29
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Blanken TF, Bathelt J, Deserno MK, Voge L, Borsboom D, Douw L. Connecting brain and behavior in clinical neuroscience: A network approach. Neurosci Biobehav Rev 2021; 130:81-90. [PMID: 34324918 DOI: 10.1016/j.neubiorev.2021.07.027] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 07/14/2021] [Accepted: 07/23/2021] [Indexed: 11/16/2022]
Abstract
In recent years, there has been an increase in applications of network science in many different fields. In clinical neuroscience and psychopathology, the developments and applications of network science have occurred mostly simultaneously, but without much collaboration between the two fields. The promise of integrating these network applications lies in a united framework to tackle one of the fundamental questions of our time: how to understand the link between brain and behavior. In the current overview, we bridge this gap by introducing conventions in both fields, highlighting similarities, and creating a common language that enables the exploitation of synergies. We provide research examples in autism research, as it accurately represents research lines in both network neuroscience and psychological networks. We integrate brain and behavior not only semantically, but also practically, by showcasing three methodological avenues that allow to combine networks of brain and behavioral data. As such, the current paper offers a stepping stone to further develop multi-modal networks and to integrate brain and behavior.
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Affiliation(s)
- Tessa F Blanken
- Department of Psychological Methods, University of Amsterdam, 1018 WT, Amsterdam, the Netherlands.
| | - Joe Bathelt
- Royal Holloway, University of London, Department of Psychology, Egham, Surrey, TW20 0EX, United Kingdom
| | - Marie K Deserno
- Max Planck Institute for Human Development, 14195, Berlin, Germany
| | - Lily Voge
- Department of Anatomy and Neurosciences, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HZ, Amsterdam, the Netherlands
| | - Denny Borsboom
- Department of Psychological Methods, University of Amsterdam, 1018 WT, Amsterdam, the Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 HZ, Amsterdam, the Netherlands; Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusets General Hospital, Boston, MA, 02129, USA
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Cooper K, Russell A, Calley S, Chen H, Kramer J, Verplanken B. Cognitive processes in autism: Repetitive thinking in autistic versus non-autistic adults. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2021; 26:849-858. [PMID: 34291680 PMCID: PMC9014768 DOI: 10.1177/13623613211034380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT A core feature of autism is the tendency to do the same activity or behaviour repetitively. We wanted to find out if autistic people also experience repetitive thinking, for example, having the same thoughts repeatedly. We thought that there would be a link between repetitive behaviour and repetitive thinking. We asked 54 autistic people and 66 non-autistic people to complete questionnaires measuring repetitive behaviours and obsessive thinking. Next, participants were trained by a researcher to record their thoughts using a structured paper form. They then completed 5 days of thought recording, which they did each time a random alarm sounded on their mobile phone. We found that autistic people had more repetitive thoughts than non-autistic people, but they did not report having more negative or visual thoughts compared with non-autistic people. Autistic people who had more repetitive thoughts during the 5 days of thought recording did not report more repetitive behaviour. However, autistic people who reported more obsessive thinking, for example, more negative and unwanted thoughts, also reported higher levels of repetitive behaviour. We conclude that some repetitive behaviours may be linked to anxiety and that more research is needed to better understand repetitive behaviours in autism.
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Martel MM, Goh PK, Lee CA, Karalunas SL, Nigg JT. Longitudinal attention-deficit/hyperactivity disorder symptom networks in childhood and adolescence: Key symptoms, stability, and predictive validity. JOURNAL OF ABNORMAL PSYCHOLOGY 2021; 130:562-574. [PMID: 34472891 PMCID: PMC8480395 DOI: 10.1037/abn0000661] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The current study visualized attention-deficit/hyperactivity disorder (ADHD) symptom networks in a longitudinal sample of participants across childhood and adolescence with exploratory examination of age and gender effects. Eight hundred thirty-six children ages 7-13 years were followed annually for 8 years in total. Across parent and teacher report, results suggested "is easily distracted" and "difficulties sustaining attention" as central symptoms across three testing points (i.e., Year 1, Year 3, and Years 5-8 collapsed). "Difficulties following instructions" and "intrudes/interrupts" also emerged as parent-reported central symptoms. Assessment of network structure across the three testing points suggested global robustness of relations among ADHD symptoms from midchildhood into early adolescence. However, relations among symptoms that cause problems in school settings (i.e., being easily distracted) were stronger in teacher-reported than parent-reported networks. When aggregated into a sum score, central symptoms during Year 1 predicted total difficulties related to mental health problems 5 years later just as well as all 18 symptoms. Central symptoms of ADHD may be useful as screeners of future emotional and behavioral difficulties. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Abstract
Empirical publications inspired by the network approach to psychopathology have increased exponentially in the twenty-first century. The central idea that an episode of mental disorder arises from causal interactions among its symptomatic elements has especially resonated with those clinical scientists whose disenchantment with traditional categorical and dimensional approaches to mental illness has become all too apparent. As the field has matured, conceptual and statistical concerns about the limitations of network approaches to psychopathology have emerged, inspiring the development of novel methods to address these concerns. Rather than reviewing the vast empirical literature, I focus instead on the issues and controversies regarding this approach and sketch directions where the field might go next.
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Affiliation(s)
- Richard J. McNally
- Department of Psychology, Harvard University, Cambridge, Massachusetts 02138, USA
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Vanzhula IA, Kinkel-Ram SS, Levinson CA. Perfectionism and Difficulty Controlling Thoughts Bridge Eating Disorder and Obsessive-Compulsive Disorder Symptoms: A Network Analysis. J Affect Disord 2021; 283:302-309. [PMID: 33578342 DOI: 10.1016/j.jad.2021.01.083] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 01/10/2021] [Accepted: 01/30/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND Eating disorders (ED) and obsessive-compulsive disorder (OCD) are highly comorbid, but little is known about how this comorbidity is maintained. Prior research suggests that obsessive thoughts and perfectionism may be shared maintenance factors for EDs and OCD. METHODS The current study used network analysis to (1) identify bridge pathways in an ED-OCD comorbidity network and (2) test if perfectionism symptoms bridge between ED-OCD symptoms in a combined network model including ED, OCD, and Perfectionism symptoms. Participants (N = 1,619) were a mixed sample of undergraduate students and individuals diagnosed with EDs. RESULTS Difficulty controlling thoughts was the symptom with the highest bridge centrality in both models, connecting with ED-related worry and doubts. In the ED-OCD-Perfectionism comorbidity network, doubts about simple everyday things and repeating things over and over bridged between ED and OCD symptoms. Additionally, specific and distinct pathways were identified between OCD and two types of ED pathology: restricting (checking compulsions and rigidity around food) and binge eating (hoarding and binge eating symptoms). LIMITATIONS Due to the cross-sectional nature of the data, no directional inferences can be made. Due to a higher OCD symptom prevalence rate than reported in previous studies, our undergraduate sample may not be representative of other college populations. CONCLUSIONS The presence of intrusive cognitions and maladaptive perfectionism may contribute to the maintenance of co-occurring ED and OCD symptoms. These findings begin to delineate specific pathways among OCD and ED symptoms, which can be used in the development of interventions to disrupt connections among these disorders.
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Affiliation(s)
- Irina A Vanzhula
- University of Louisville, Department of Psychological & Brain Sciences
| | | | - Cheri A Levinson
- University of Louisville, Department of Psychological & Brain Sciences.
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Hollestein V, Buitelaar JK, Brandeis D, Banaschewski T, Kaiser A, Hohmann S, Oranje B, Gooskens B, Durston S, Williams SCR, Lythgoe DJ, Naaijen J. Developmental changes in fronto-striatal glutamate and their association with functioning during inhibitory control in autism spectrum disorder and obsessive compulsive disorder. NEUROIMAGE-CLINICAL 2021; 30:102622. [PMID: 33765540 PMCID: PMC8022251 DOI: 10.1016/j.nicl.2021.102622] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 02/16/2021] [Accepted: 03/03/2021] [Indexed: 12/18/2022]
Abstract
Multi-center, longitudinal, transdiagnostic study of glutamate and neural activity. Differing roles of glutamate on activity in striatum during inhibitory control. Glutamate concentrations in ACC decrease over time in ASD adolescents. Differing neural mechanisms of compulsivity in OCD and repetitive behaviors in ASD.
Autism spectrum disorder (ASD) and obsessive compulsive disorder (OCD) show overlapping symptomatology and deficits in inhibitory control, which are associated with altered functioning and glutamatergic signaling in fronto-striatal circuitry. These parameters have never been examined together. The purpose of the current study was to investigate functioning during inhibitory control and its association with fronto-striatal glutamate concentrations across these disorders using a multi-center, longitudinal approach. Adolescents with ASD (n = 24), OCD (n = 15) and controls (n = 35) underwent two magnetic resonance imaging (MRI) sessions with a one-year interval. This included proton magnetic resonance spectroscopy (1H-MRS; n = 74) and functional MRI during an inhibitory control task (n = 53). We investigated 1H-MRS data and fMRI data separately as well as integrated in a multimodal analysis using linear models focusing on diagnosis and continuous measures of overlapping compulsivity symptoms. ACC glutamate was reduced over time in the ASD group compared with controls, while striatal glutamate decreased over time independent of diagnosis. Increased compulsive behavior seemed to be associated with increased striatal activity during failed inhibitory control. The integrated analyses showed differential involvement of increased striatal glutamate during failed but decreased striatal glutamate during successful inhibitory control in the OCD group compared to controls and ASD, suggesting different underlying mechanisms for OCD compared to ASD.
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Affiliation(s)
- Viola Hollestein
- Department of Cognitive Neuroscience, Donders Institute of Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands.
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute of Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands; Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands.
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland; Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland; ETH Zurich, Zurich, Switzerland.
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany.
| | - Anna Kaiser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany.
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty, Mannheim/Heidelberg University, Mannheim, Germany.
| | - Bob Oranje
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Bram Gooskens
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Sarah Durston
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Steven C R Williams
- Department of Neuroimaging, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom.
| | - David J Lythgoe
- Department of Neuroimaging, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom.
| | - Jilly Naaijen
- Department of Cognitive Neuroscience, Donders Institute of Brain, Cognition and Behaviour, Radboud University Medical Center, the Netherlands; Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands.
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Jones PJ, Ma R, McNally RJ. Bridge Centrality: A Network Approach to Understanding Comorbidity. MULTIVARIATE BEHAVIORAL RESEARCH 2021; 56:353-367. [PMID: 31179765 DOI: 10.1080/00273171.2019.1614898] [Citation(s) in RCA: 444] [Impact Index Per Article: 148.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Recently, researchers in clinical psychology have endeavored to create network models of the relationships between symptoms, both within and across mental disorders. Symptoms that connect two mental disorders are called "bridge symptoms." Unfortunately, no formal quantitative methods for identifying these bridge symptoms exist. Accordingly, we developed four network statistics to identify bridge symptoms: bridge strength, bridge betweenness, bridge closeness, and bridge expected influence. These statistics are nonspecific to the type of network estimated, making them potentially useful in individual-level psychometric networks, group-level psychometric networks, and networks outside the field of psychopathology such as social networks. We first tested the fidelity of our statistics in predicting bridge nodes in a series of simulations. Averaged across all conditions, the statistics achieved a sensitivity of 92.7% and a specificity of 84.9%. By simulating datasets of varying sample sizes, we tested the robustness of our statistics, confirming their suitability for network psychometrics. Furthermore, we simulated the contagion of one mental disorder to another, showing that deactivating bridge nodes prevents the spread of comorbidity (i.e., one disorder activating another). Eliminating nodes based on bridge statistics was more effective than eliminating nodes high on traditional centrality statistics in preventing comorbidity. Finally, we applied our algorithms to 18 group-level empirical comorbidity networks from published studies and discussed the implications of this analysis.
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Affiliation(s)
| | - Ruofan Ma
- Department of Psychology, University of Waterloo
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Sahlan RN, Williams BM, Forrest LN, Saunders JF, Fitzsimmons-Craft EE, Levinson CA. Disordered eating, self-esteem, and depression symptoms in Iranian adolescents and young adults: A network analysis. Int J Eat Disord 2021; 54:132-147. [PMID: 32865853 PMCID: PMC8159574 DOI: 10.1002/eat.23365] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 07/30/2020] [Accepted: 07/30/2020] [Indexed: 12/23/2022]
Abstract
OBJECTIVE The network theory of psychopathology examines networks of interconnections across symptoms. Several network studies of disordered eating have identified central and bridge symptoms in Western samples, yet network models of disordered eating have not been tested in non-Western samples. The current study tested a network model of disordered eating in Iranian adolescents and college students, as well as models of co-occurring depression and self-esteem. METHOD Participants were Iranian college students (n= 637) and adolescents (n = 1,111) who completed the Eating Disorder Examination-Questionnaire (EDE-Q), Rosenberg Self-Esteem Scale (RSES) and Beck Depression Inventory, Second Edition (BDI-II). We computed six Glasso networks and identified central and bridge symptoms. RESULTS Central disordered eating nodes in most models were a desire to lose weight and discomfort when seeing one's own body. Central self-esteem and depression nodes were feeling useless and self-dislike, respectively. Feeling like a failure was the most common bridge symptom between disordered eating and depression symptoms. With exception of a few differences in some edges, networks did not significantly differ in structure. DISCUSSION Desire to lose weight was the most central node in the networks, which is consistent with sociocultural theories of disordered eating development, as well as prior network models from Western-culture samples. Feeling like a failure was the most central bridge symptom between depression and disordered eating, suggesting that very low self-esteem may be a shared correlate or risk factor for disordered eating and depression in Iranian adolescents and young adults.
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Affiliation(s)
- Reza N. Sahlan
- Department of Clinical Psychology, Iran University of Medical Sciences, Tehran, Iran
| | - Brenna M. Williams
- Department of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA
| | | | | | | | - Cheri A. Levinson
- Department of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA
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Deserno MK, Borsboom D, Begeer S, van Bork R, Hinne M, Geurts HM. Highways to happiness for autistic adults? Perceived causal relations among clinicians. PLoS One 2020; 15:e0243298. [PMID: 33320901 PMCID: PMC7737981 DOI: 10.1371/journal.pone.0243298] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 11/18/2020] [Indexed: 11/19/2022] Open
Abstract
The network approach to psychological phenomena advances our understanding of the interrelations between autism and well-being. We use the Perceived Causal Relations methodology in order to (i) identify perceived causal pathways in the well-being system, (ii) validate networks based on self-report data, and (iii) quantify and integrate clinical expertise in autism research. Trained clinicians served as raters (N = 29) completing 374 cause-effects ratings of 34 variables on well-being and symptomatology. A subgroup (N = 16) of raters chose intervention targets in the resulting network which we found to match the respective centrality of nodes. Clinicians' perception of causal relations was similar to the interrelatedness found in self-reported client data (N = 323). We present a useful tool for translating clinical expertise into quantitative information enabling future research to integrate this in scientific studies.
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Affiliation(s)
- Marie K. Deserno
- Dr. Leo Kannerhuis and REACH-AUT, Doorwerth, The Netherlands
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Denny Borsboom
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Sander Begeer
- Section Clinical Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Riet van Bork
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Max Hinne
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Hilde M. Geurts
- Dr. Leo Kannerhuis and REACH-AUT, Doorwerth, The Netherlands
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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Vandewouw MM, Choi E, Hammill C, Arnold P, Schachar R, Lerch JP, Anagnostou E, Taylor MJ. Emotional face processing across neurodevelopmental disorders: a dynamic faces study in children with autism spectrum disorder, attention deficit hyperactivity disorder and obsessive-compulsive disorder. Transl Psychiatry 2020; 10:375. [PMID: 33139709 PMCID: PMC7608673 DOI: 10.1038/s41398-020-01063-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/14/2020] [Accepted: 04/21/2020] [Indexed: 12/12/2022] Open
Abstract
Autism spectrum disorder (ASD) is classically associated with poor face processing skills, yet evidence suggests that those with obsessive-compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) also have difficulties understanding emotions. We determined the neural underpinnings of dynamic emotional face processing across these three clinical paediatric groups, including developmental trajectories, compared with typically developing (TD) controls. We studied 279 children, 5-19 years of age but 57 were excluded due to excessive motion in fMRI, leaving 222: 87 ASD, 44 ADHD, 42 OCD and 49 TD. Groups were sex- and age-matched. Dynamic faces (happy, angry) and dynamic flowers were presented in 18 pseudo-randomized blocks while fMRI data were collected with a 3T MRI. Group-by-age interactions and group difference contrasts were analysed for the faces vs. flowers and between happy and angry faces. TD children demonstrated different activity patterns across the four contrasts; these patterns were more limited and distinct for the NDDs. Processing happy and angry faces compared to flowers yielded similar activation in occipital regions in the NDDs compared to TDs. Processing happy compared to angry faces showed an age by group interaction in the superior frontal gyrus, increasing with age for ASD and OCD, decreasing for TDs. Children with ASD, ADHD and OCD differentiated less between dynamic faces and dynamic flowers, with most of the effects seen in the occipital and temporal regions, suggesting that emotional difficulties shared in NDDs may be partly attributed to shared atypical visual information processing.
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Affiliation(s)
- Marlee M Vandewouw
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
| | - EunJung Choi
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Bloorview Research Institute, University of Toronto, 150 Kilgour Road, Toronto, Canada
| | - Christopher Hammill
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
| | - Paul Arnold
- Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Alberta, Canada
| | - Russell Schachar
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Department of Psychiatry, Hospital for Sick Children, Toronto, Canada
| | - Jason P Lerch
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Evdokia Anagnostou
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Bloorview Research Institute, University of Toronto, 150 Kilgour Road, Toronto, Canada
| | - Margot J Taylor
- Department of Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada.
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada.
- Department of Psychology, University of Toronto, Toronto, Canada.
- Department of Medical Imaging, University of Toronto, Toronto, Canada.
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Beyond diagnosis: Cross-diagnostic features in canonical resting-state networks in children with neurodevelopmental disorders. NEUROIMAGE-CLINICAL 2020; 28:102476. [PMID: 33201803 PMCID: PMC7649647 DOI: 10.1016/j.nicl.2020.102476] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 10/15/2020] [Accepted: 10/17/2020] [Indexed: 11/24/2022]
Abstract
Resting-state connectivity did not differ across neurodevelopmental disorders. General adaptive function across all participants related to subcortical connectivity. Participants in the same data-driven clusters were highly heterogeneous in diagnosis. Neurobiological similarity and dissimilarity may be seen in beyond-diagnosis categories.
Children with neurodevelopmental disorders (NDDs) share common behavioural manifestations despite distinct categorical diagnostic criteria. Here, we examined canonical resting-state network connectivity in three diagnostic groups (autism spectrum disorder, attention-deficit/hyperactivity disorder and paediatric obsessive–compulsive disorder) and typically developing controls (TD) in a large single-site sample (N = 407), applying diagnosis-based and dimensional approaches to understand underlying neurobiology across NDDs. Each participant’s functional network graphs were computed using five graph metrics. In diagnosis-based comparisons, an analysis of covariance was performed to compare all NDDs to TD, followed by pairwise comparisons between NDDs. In the dimensional approach, participants’ functional network graphs were correlated with continuous behavioural measures, and a data-driven k-means clustering analysis was applied to determine if subgroups of participants were seen, without diagnostic information having been included. In the diagnosis-based comparisons, children with NDDs did not differ significantly from the TD group and the NDD categorical groups also did not differ significantly from each other, across all graph metrics. In the dimensional, diagnostic-independent approach, however, subcortical functional connectivity was significantly correlated with participants’ general adaptive functioning across all participants. The clustering analysis identified an optimal solution of two clusters, and participants assigned in the same data-driven cluster were highly heterogeneous in diagnosis. Neither cluster exclusively contained a specific diagnostic group, nor did NDDs separate cleanly from TDs. Each participant’s distance ratio between the two clusters was significantly correlated with general adaptive functioning, social deficits and attentional problems. Our results suggest the neurobiological similarity and dissimilarity between NDDs need to be investigated beyond DSM/ICD-based, behaviourally-defined diagnostic categories.
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Hirota T, McElroy E, So R. Network Analysis of Internet Addiction Symptoms Among a Clinical Sample of Japanese Adolescents with Autism Spectrum Disorder. J Autism Dev Disord 2020; 51:2764-2772. [PMID: 33040268 DOI: 10.1007/s10803-020-04714-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
In the present study, we employed network analysis that conceptualizes internet addiction (IA) as a complex network of mutually influencing symptoms in 108 adolescents with autism spectrum disorder (ASD) to examine the network architecture of IA symptoms and identify central/influential symptoms. Our analysis revealed that defensive and secretive behaviors and concealment of internet use were identified as central symptoms in this population, suggesting that mitigating these symptoms potentially prevent the development and/or maintenance of IA in adolescents with ASD. Providing adolescents and their caregivers with psychoeducation on the role of central symptoms above in IA can be a salient intervention. Doing so may facilitate nonconflicting conversations between them about adolescents' internet use and promote more healthy adolescents' internet use behavior.
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Affiliation(s)
- Tomoya Hirota
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, 401 Parnassus Ave, San Francisco, CA, USA.
| | - Eoin McElroy
- Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Ryuhei So
- Department of Psychiatry, Okayama Psychiatric Medical Center, Okayama, Japan.,Health Promotion and Human Behavior, Graduate School of Medicine / School of Public Health, Kyoto University, Kyoto, Japan
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Bedford SA, Hunsche MC, Kerns CM. Co-occurrence, Assessment and Treatment of Obsessive Compulsive Disorder in Children and Adults With Autism Spectrum Disorder. Curr Psychiatry Rep 2020; 22:53. [PMID: 32803413 DOI: 10.1007/s11920-020-01176-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE OF REVIEW This review aims to give an update on research in the past 5 years regarding the co-occurrence, assessment and treatment of obsessive compulsive disorder (OCD) in individuals with autism spectrum disorder (ASD). RECENT FINDINGS Recent findings affirm not only a high prevalence of OCD amongst individuals with ASD (and vice versa) but also notable variability in assessment methods and results. There remain limited validated measures with which to assess OCD in those with ASD, which are often difficult to differentiate. Adapted and function-based CBT programs specifically designed for ASD demonstrate promising results, but additional randomised controlled trials are needed. Though some exciting progress has been made in the area of treatment of OCD in ASD, progress remains hampered by inconsistent measurement of OCD in ASD. Future priorities include development of brief, valid assessment tools and determining the efficacy and effectiveness of newly developed and adapted treatment programs.
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Affiliation(s)
- Saashi A Bedford
- Department of Psychology, University of British Columbia, Vancouver, BC, Canada
| | - Michelle C Hunsche
- Department of Psychology, University of British Columbia, Vancouver, BC, Canada
| | - Connor M Kerns
- Department of Psychology, University of British Columbia, Vancouver, BC, Canada.
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Goh PK, Lee CA, Martel MM, Fillmore MT, Derefinko KJ, Lynam DR. Conceptualizing the UPPS‐P model of impulsive personality through network analysis: Key dimensions and general robustness across young adulthood. J Pers 2020; 88:1302-1314. [DOI: 10.1111/jopy.12572] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 04/14/2020] [Accepted: 06/24/2020] [Indexed: 12/20/2022]
Affiliation(s)
- Patrick K. Goh
- Department of Psychology University of Kentucky Lexington KY USA
| | - Christine A. Lee
- Division of Behavioral Medicine and Clinical Psychology Cincinnati Children's Hospital Medical Center Cincinnati OH USA
| | | | - Mark T. Fillmore
- Department of Psychology University of Kentucky Lexington KY USA
| | - Karen J. Derefinko
- Department of Preventative Medicine University of Tennessee Health Science Center Memphis TN USA
| | - Donald R. Lynam
- Department of Psychological Sciences Purdue University West Lafayette IN USA
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Repetitive Behavior in Children and Adolescents: Psychometric Properties of the German Version of the Repetitive Behavior Scale-Revised. J Autism Dev Disord 2020; 51:1224-1237. [PMID: 32642960 DOI: 10.1007/s10803-020-04588-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Restricted repetitive behaviors (RRBs) are a core feature of autism spectrum disorders (ASD) and further occur in intellectual disability (ID), mental disorders (MD), and in typically developed people (TD). There is a need of a valid and reliable measure to record RRBs as transdiagnostic symptom, which captures RRBs heterogeneity and evaluates severity. The Repetitive Behavior Scale-Revised (RBS-R) is an established screening instrument for RRBs, but was predominantly limited to ASD samples. We examined the psychometric properties of the German version of the RBS-R in 948 participants with ASD, ID, MD and TD aged 4 to 17 years. The suitability was proofed delivering a four-factor solution, good internal consistency, external validity as well as group, age, and sex effects.
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Cervin M, Perrin S, Olsson E, Aspvall K, Geller DA, Wilhelm S, McGuire J, Lázaro L, Martínez-González AE, Barcaccia B, Pozza A, Goodman WK, Murphy TK, Seçer İ, Piqueras JA, Rodríguez-Jiménez T, Godoy A, Rosa-Alcázar AI, Rosa-Alcázar Á, Ruiz-García BM, Storch EA, Mataix-Cols D. The Centrality of Doubting and Checking in the Network Structure of Obsessive-Compulsive Symptom Dimensions in Youth. J Am Acad Child Adolesc Psychiatry 2020; 59:880-889. [PMID: 31421234 PMCID: PMC7219532 DOI: 10.1016/j.jaac.2019.06.018] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 06/24/2019] [Accepted: 07/10/2019] [Indexed: 01/09/2023]
Abstract
OBJECTIVE Obsessive-compulsive disorder (OCD) is a heterogeneous condition with well-established symptom dimensions across the lifespan. The objective of the present study was to use network analysis to investigate the internal structure of these dimensions in unselected schoolchildren and in children with OCD. METHOD We estimated the network structure of OCD symptom dimensions in 6,991 schoolchildren and 704 children diagnosed with OCD from 18 sites across 6 countries. All participants completed the Obsessive-Compulsive Inventory-Child Version. RESULTS In both the school-based and clinic-based samples, the OCD dimensions formed an interconnected network with doubting/checking emerging as a highly central node, that is, having strong connections to other symptom dimensions in the network. The centrality of the doubting/checking dimension was consistent across countries, sexes, age groups, clinical status, and tic disorder comorbidity. Network differences were observed for age and sex in the school-based but not the clinic-based samples. CONCLUSION The centrality of doubting/checking in the network structure of childhood OCD adds to classic and recent conceptualizations of the disorder in which the important role of doubt in disorder severity and maintenance is highlighted. The present results suggest that doubting/checking is a potentially important target for further research into the etiology and treatment of childhood OCD.
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Affiliation(s)
- Matti Cervin
- Lund University, Lund, Sweden; Skåne Child and Adolescent Psychiatry, Lund, Sweden.
| | | | - Elin Olsson
- Skåne Child and Adolescent Psychiatry, Lund, Sweden
| | - Kristina Aspvall
- Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - Daniel A Geller
- Massachusetts General Hospital and Harvard Medical School, Boston Massachusetts
| | - Sabine Wilhelm
- Massachusetts General Hospital and Harvard Medical School, Boston Massachusetts
| | - Joseph McGuire
- Johns Hopkins University School of Medicine, Baltimore Maryland
| | - Luisa Lázaro
- Hospital Clínic, IDIBAPS, CIBERSAM, University of Barcelona, Spain
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - David Mataix-Cols
- Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
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Lai PT, Ng R, Bellugi U. Parental report of cognitive and social-emotionality traits in school-age children with autism and Williams syndrome. INTERNATIONAL JOURNAL OF DEVELOPMENTAL DISABILITIES 2020; 68:309-316. [PMID: 35603004 PMCID: PMC9122353 DOI: 10.1080/20473869.2020.1765296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Revised: 03/28/2020] [Accepted: 04/30/2020] [Indexed: 06/15/2023]
Abstract
The majority of the research examining children with Autism Spectrum Disorder (ASD) and Williams Syndrome (WS) focus on the social domain while few have examined cognitive style and emotionality. Accordingly, this current study assessed the day-to-day cognitive and behavioral functioning of school-age children with ASD, WS, and neurotypical development (ND) through caregiver-report inventories to further delineate commonalities and disparities in cognitive and social-emotional traits. Two caregiver-report inventories, the Children's Behavior Questionnaire and the Multidimensional Personality Questionnaire were employed to assess the day-to-day functioning of children ages 7-14 years. Participants included 64 caregivers of children, of these, 25 were caregivers of children with high functioning autism (HFA), 14 with WS, and 25 with ND. Multivariate analysis of covariance was computed to assess between-group differences for each subscale within a questionnaire. Covariates included age and full-scale IQ. For cognitive traits, group differences were observed across two categories while seven were present within the social-emotional categories. The majority of the group effects reflected differences in social-emotional traits between ND and both neurodevelopmental groups, while limited distinctions were found between the two clinical groups. This brief report provides additional evidence that HFA and WS may show similarities in cognitive traits but more divergent social-emotional tendencies, despite controlling for age and intellect. This study highlights the large social-emotional differences that supports prior phenotypic descriptions of both neurodevelopmental groups. Future research in these domains are needed to determine focused interventions to address social impairment.
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Affiliation(s)
- Philip T. Lai
- Joint Doctoral Program in Language and Communicative Disorders, School of Speech, Language, and Hearing Sciences, San Diego State University, San Diego, CA, USA
- Joint Doctoral Program in Language and Communicative Disorders, Center for Research in Language, University of California San Diego, La Jolla, CA, USA
- Laboratory for Cognitive Neuroscience, Salk Institute for Biological Sciences, La Jolla, CA, USA
| | - Rowena Ng
- Laboratory for Cognitive Neuroscience, Salk Institute for Biological Sciences, La Jolla, CA, USA
- Institute of Child Development, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Ursula Bellugi
- Laboratory for Cognitive Neuroscience, Salk Institute for Biological Sciences, La Jolla, CA, USA
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Gysi DM, Nowick K. Construction, comparison and evolution of networks in life sciences and other disciplines. J R Soc Interface 2020; 17:20190610. [PMID: 32370689 PMCID: PMC7276545 DOI: 10.1098/rsif.2019.0610] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 04/09/2020] [Indexed: 12/12/2022] Open
Abstract
Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics. Many networks change over time, be it within seconds or millions of years, depending on the nature of the network. Our focus will be on comparative network analyses in life sciences, where deciphering temporal network changes is a core interest of molecular, ecological, neuropsychological and evolutionary biologists. Further, we will take a journey through different disciplines, such as social sciences, finance and computational gastronomy, to present commonalities and differences in how networks change and can be analysed. Finally, we envision how borrowing ideas from these disciplines could enrich the future of life science research.
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Affiliation(s)
- Deisy Morselli Gysi
- Department of Computer Science, Interdisciplinary Center of Bioinformatics, University of Leipzig, 04109 Leipzig, Germany
- Swarm Intelligence and Complex Systems Group, Faculty of Mathematics and Computer Science, University of Leipzig, 04109 Leipzig, Germany
- Center for Complex Networks Research, Northeastern University, 177 Huntington Avenue, Boston, MA 02115, USA
| | - Katja Nowick
- Human Biology Group, Institute for Biology, Faculty of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Königin-Luise-Straβe 1-3, 14195 Berlin, Germany
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Lydon-Staley DM, Schnoll RA, Hitsman B, Bassett DS. The Network Structure of Tobacco Withdrawal in a Community Sample of Smokers Treated With Nicotine Patch and Behavioral Counseling. Nicotine Tob Res 2020; 22:408-414. [PMID: 30452739 PMCID: PMC7297103 DOI: 10.1093/ntr/nty250] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 11/14/2018] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Network theories of psychopathology highlight that, rather than being indicators of a latent disorder, symptoms of disorders can causally interact with one another in a network. This study examined tobacco withdrawal from a network perspective. METHODS Participants (n = 525, 50.67% female) completed the Minnesota Tobacco Withdrawal Scale four times (2 weeks prior to a target quit day, on the target quit day, and 4 and 8 weeks after the target quit day) over the course of 8 weeks of treatment with nicotine patch and behavioral counseling within a randomized clinical trial testing long-term nicotine patch therapy in treatment-seeking smokers. The conditional dependence among seven withdrawal symptoms was estimated at each of the four measurement occasions. Influential symptoms of withdrawal were identified using centrality indices. Changes in network structure were examined using the Network Comparison Test. RESULTS Findings indicated many associations among the individual symptoms of withdrawal. The strongest associations that emerged were between sleep problems and restlessness, and associations among affective symptoms. Restlessness and affective symptoms emerged as the most central symptoms in the withdrawal networks. Minimal differences in the structure of the withdrawal networks emerged across time. CONCLUSIONS The cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal rather than simply reflecting passive indicators of a latent disorder. Findings encourage greater consideration of individual withdrawal symptoms and their potential interactions and may be used to generate hypotheses that may be tested in future intensive longitudinal studies. IMPLICATIONS This study provides a novel, network perspective on tobacco withdrawal. Drawing on network theories of psychopathology, we suggest that the cooccurrence of withdrawal symptoms may result from interactions among symptoms of withdrawal over time, rather than simply reflecting passive indicators of a latent disorder. Results indicating many associations among individual symptoms of withdrawal are consistent with a network perspective. Other results of interest include minimal changes in the network structure of withdrawal across four measurement occasions prior to and during treatment with nicotine patch and behavioral counseling.
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Affiliation(s)
- David M Lydon-Staley
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA
| | - Robert A Schnoll
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Brian Hitsman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA
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Weintraub MJ, Schneck CD, Miklowitz DJ. Network analysis of mood symptoms in adolescents with or at high risk for bipolar disorder. Bipolar Disord 2020; 22:128-138. [PMID: 31729789 PMCID: PMC7085972 DOI: 10.1111/bdi.12870] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Network analyses of psychopathology examine the relationships between individual symptoms in an attempt to establish the causal interactions between symptoms that may give rise to episodes of psychiatric disorders. We conducted a network analysis of mood symptoms in adolescents with or at risk for bipolar spectrum disorders. METHODS The sample consisted of 272 treatment-seeking adolescents with or at high risk for bipolar disorder who had at least subsyndromal depressive or (hypo)manic symptoms. Based on symptom scores assessed via semi-structured interviews, we constructed the network of depressive and manic symptoms and identified the most central symptoms and symptom communities within the network. We used bootstrapping analyses to determine the reliability of network parameters. RESULTS Symptoms within the depressive and manic mood poles were more related to each other than to symptoms of the opposing mood pole. Four communities were identified, including a depressive symptom community and three manic symptom communities. Fatigue and depressed mood were the strongest individual symptoms within the overall network (ie the most highly correlated with other symptoms), followed by motor hyperactivity. Mood lability and irritability were found to be "bridge" symptoms that connected the two mood poles. CONCLUSIONS Symptoms of activity/energy (ie fatigue and hyperactivity) and depressed mood are the most prominent mood symptoms among youth with bipolar spectrum disorders. Mood lability and irritability represent potential warning signs of emergent episodes of either polarity. Targeting these central and bridge symptoms would lead to more efficient assessments and therapeutic interventions for bipolar disorder.
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Affiliation(s)
- Marc J. Weintraub
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Christopher D. Schneck
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - David J. Miklowitz
- Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
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Robinaugh DJ, Hoekstra RHA, Toner ER, Borsboom D. The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research. Psychol Med 2020; 50:353-366. [PMID: 31875792 PMCID: PMC7334828 DOI: 10.1017/s0033291719003404] [Citation(s) in RCA: 279] [Impact Index Per Article: 69.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.
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Affiliation(s)
- Donald J. Robinaugh
- Massachusetts General Hospital, Department of Psychiatry
- Harvard Medical School
| | | | - Emma R. Toner
- Massachusetts General Hospital, Department of Psychiatry
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